In the modern era, there is an increasing demand in various entities of the service industry for tools and techniques which facilitate better services and unmatched experiences to valued users. However, existing technologies dealing with tracking of user equipment associated with valued users operating in various locations across various segments lack one or more necessary features. Examples of various segments may include healthcare, insurance, automotive, travel agency, retail stores, apparel showrooms etc. For instance, a user equipment associated with a valued user using one of the services at a particular location, out of various services at various locations provided by a business entity may be identified only at that particular location, however, the same user equipment may not be identified as associated with the valued user at other locations or for other business segments, leading to user dissatisfaction. Such problems arise due to inefficient user data integration methods for data obtained from myriad sources. Further, it has been observed that traditional systems employing fragmented user data analytics fails to provide for optimal tracking and identification of user equipment.
In light of the aforementioned drawbacks, there is a need for a system and method for efficiently tracking and identifying user equipment across various segments of a business entity at various locations. There is a need for system and method which provides improved user data integration and analytics for optimally tracking and identifying user equipment associated with valued users. Yet further, there is need for a system and method which can be easily integrated with existing systems.